Results 101 to 110 of about 20,046 (244)

PlaceRaider: Virtual Theft in Physical Spaces with Smartphones [PDF]

, 2012
As smartphones become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of smartphone features increasingly powerful onboard sensor suites.
Crandall, David, Kapadia, Apu, Rahman, Zahid, Templeman, Robert   +3 more
core  

Automatic Generation of MAEC and STIX Standards for Android Malware Threat Intelligence [PDF]

, 2020
Jungsoo Park, Long Nguyen-Vu, George Bencivengo, Souhwan Jung   +3 more
openalex   +1 more source

Investigation of Android Malware Using Deep Learning Approach [PDF]

, 2022
V. Joseph Raymond, Ritik Raj
openalex   +1 more source

Not so Crisp, Malware! Fuzzy Classification of Android Malware Classes

2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2018
Mobile devices have been spreading at great rate in recent years. Not only smartphone, but also tablets and IoT devices, are gaining an increasingly place in our everyday lives. This is the reason why attackers are developing more and more aggressive techniques with the aim to exfiltrate our sensitive and private information.
Mercaldo F., Saracino A.
openaire   +4 more sources

An Effective Temporal Convolutional Networks-Based Method for Detecting Android Malware Using Dynamic Extracted Features

IEEE Access
With an increase in the number and complexity of malware, traditional malware detection methods such as heuristic-based and signature-based ones have become less adequate, leaving user applications vulnerable.
Abdurraheem Joomye, Mee Hong Ling, Muhammed Basheer Jasser, Athirah Mohd Ramly, Kok-Lim Alvin Yau   +4 more
doaj   +1 more source

Malceiver: Perceiver with Hierarchical and Multi-modal Features for Android Malware Detection [PDF]

, 2022
Niall McLaughlin
openalex   +1 more source

A3CM: Automatic Capability Annotation for Android Malware

IEEE Access, 2019
Android malware poses serious security and privacy threats to the mobile users. Traditional malware detection and family classification technologies are becoming less effective due to the rapid evolution of the malware landscape, with the emerging of so ...
Junyang Qiu, Jun Zhang, Wei Luo, Lei Pan, Surya Nepal, Yu Wang, Yang Xiang   +6 more
doaj   +1 more source

Android Malware Detection Based on Sensitive Patterns

, 2022
Hui Li, Hailing Zhang, Xue Chen, Dan Liao, Ming Zhang   +4 more
openalex   +1 more source

MADRAS-NET: A deep learning approach for detecting and classifying android malware using Linknet

Measurement: Sensors
Malware is an intentionally created malicious software that still poses a serious threat in cyberspace. Android malware has become one of the most significant online threats in recent years due to its increase in prevalence. Even though a lot of work has
Yi Wang, Shanshan Jia
doaj   +1 more source

Detecção de Malwares Android: Levantamento Empırico da Disponibilidade e da Atualização das Fontes de Dados

, 2022
Tainá Soares, Joner Mello, Lucas Barcellos, Renato Sayyed, Guilherme Siqueira, Karina Casola, Estevão Costa, Nicolas Neves, Eduardo Feitosa, Diego Kreutz   +9 more
openalex   +1 more source